Internet of Things process selection: AHP selection method

Autor(es)

Durao, Luiz Fernando C. S. ; Carvalho, Marly M. ; Takey, Silvia ; Cauchick-Miguel, Paulo A. ; Zancul, Eduardo

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY; v. 99, n. 9-12, p. 12-pg., 2018-12-01.

Resumo

The Internet of Things (IoT) has become an important agenda in the advanced manufacturing environment. In order to encourage IoT application and assure an appropriate selection of processes to be improved by IoT technology, a group of analysis criteria must be highlighted to give the companies a tool to perform the correct selection. This study aims to propose a model for selecting IoT technology. The research design combines a systematic literature review, applying bibliometrics and content analysis, with case application and refinement. An application was carried out in an IoT hardware company, incorporating it at a solvent recycling machine. A second application was performed in a seedling selection machine producer. As a result, a model for selecting IoT technology is presented, which consists of four phasesprocess modeling, grading, weighting, and final selection. The model applies an analytic hierarchy process (AHP) based on the following criteria: reliability, security, business, mobility, and heterogeneity. The results also suggest IoT selection is related to the ability of combining different criteria related to the system and technology selection to install IoT solutions. Finally, issues related to the system characteristics other than technology are becoming more cited in the literature in the last 5years concluding that selecting IoT technology is a complex activity that needs to be improved, especially in the years to come. (AU)

• Processo FAPESP: 16/50062-0 - Aplicação de tecnologia de Internet das coisas para viabilização de sistemas produto-serviço (PSS)
• Beneficiário: Sílvia Mayumi Takey Dellamano
• Modalidade de apoio: Auxílio à Pesquisa - Pesquisa Inovativa em Pequenas Empresas - PIPE